Centralized method for near-field distance measurement for use in a networked ecosystem

Abstract

A centralized, extended near-field distance measurement method for use in a networked ecosystem with an initiator node in an initiator network, relay nodes, and a target node in a target network involves accessing a recorded activation profile. The ecosystem can be structured as an Internet of Things (IoT) ecosystem. The activation profile contains a desired action or service of the target node, such as an automation robot. A near-field distance measurement protocol estimates the distance to one or more neighboring relay nodes within a maximum range of the initiator node. The target node lies outside this maximum range. The method includes identifying a distance measurement path between the initiator and target nodes, including the transmission of distance measurement parameters between nodes of the initiator and target networks.The distance measurement path includes the designated node. The procedure includes requesting the execution of the desired action or service via the distance measurement path.

Description

[0001] The present invention relates to a centralized method for near-field distance measurement for use in a networked ecosystem. INTRODUCTION

[0002] Advances in global automation technology have led to the introduction of network-based management for a wide range of storage, diagnostic, maintenance, sensor, drive, control, and other processes and operations. For example, charging processes for modern electric vehicles (EVs) or plug-in hybrid electric vehicles (PHEVs) can be scheduled at home and managed via a "smart garage" or workshop network connection. Other aspects of smart workshop automation include smartphone-based monitoring and opening / closing of garage doors, as well as control of climate settings such as temperature, humidity, and air quality. Security systems can also be managed remotely.In a representative workshop environment, such automation also simplifies the management of inventory, tools, and parts, as well as a range of other functions. Similar technologies can also be used in other environments, such as the user's home or office.

[0003] The effective implementation of global automation solutions depends on accurate near-field distance measurement, or proximity ranging, between connected devices, commonly referred to as communication nodes. In the context of global smart workshop automation and other exemplary applications of the Internet of Things (IoT), the term "proximity ranging" generally refers to the process of determining the distance between such nodes. Common near-field distance measurement methods that utilize electromagnetic waves include estimating the distance between a transmitter and a receiver based on the received signal strength, estimating the time a packet sent by the transmitter takes to reach the receiver (i.e., flight time), and other methods. The transmitted signals can be ultra-wideband (UWB) or ultra-wideband (UW) signals.These technologies include ultra-wideband, Bluetooth Low Energy (BLE), Wi-Fi, and others. However, these techniques are only capable of measuring the near-field distance between two devices that are in close proximity. For some emerging IoT use cases in the consumer or industrial sectors that require low latency, or where not all IoT devices belong to the same network or trust circle, such limits to range measurements can lead to a suboptimal user experience.

[0004] For further background information, reference is made in advance to the publications US 2019 / 0 245 707 A1 and US 2019 / 0 037 419 A1. SUMMARY

[0005] The present invention relates to a centralized near-field distance measurement protocol for use in a local networked ecosystem. The solutions presented here—hereinafter referred to as "multi-hop" proximity ranging or near-field distance measurement—are intended to address potentially problematic aspects such as latency, range, security / privacy, out-of-range service activation, network congestion, and suboptimal customer experience in an Internet of Things (IoT) environment, e.g., in the global smart garage application mentioned above, or in industrial applications where devices located in different wireless networks (possibly in different buildings or operational areas) need to communicate with each other.The proposed centralized near-field distance measurement protocol can be used to control end-to-end proximity ranging in the aforementioned local networked ecosystem, where an initiator node requests multiple connected relay nodes to estimate the distance to an out-of-range target node. The disclosed protocol can be implemented to dynamically estimate the distance between the initiator and target nodes using a centralized model, embodiments of which are described in detail below.

[0006] The centralized approach involves the use of a central controller, such as a cloud-based server, a backend device, or a local server, that can communicate with the target node for the service activation described above. Without cloud or on-premises communication between different buildings, range-based applications, for example, are generally not feasible in a multi-building scenario. In cases where nodes / devices requiring distance measurement are not located together in a communication network, the present strategy, using the central controller, can locate one or more intermediate nodes and thereby perform an extended multi-hop distance measurement according to the invention.

[0007] According to the invention, a centralized method for near-field distance measurement for use in a networked ecosystem is presented, characterized by the features of claim 1.

[0008] In a particular embodiment, a centralized near-field distance measurement method and an associated networked ecosystem are disclosed herein. The networked ecosystem comprises an initiator node located in / on a first wireless network (“Initiator Network”). The networked ecosystem includes a plurality of relay nodes, including a designated node, and a target node located in a second wireless network (“Target Network”). The target node is located outside the range of the initiator node. In one possible embodiment, the centralized distance measurement method comprises accessing a recorded activation profile in / from a computer-readable storage medium as a desired action or service of the target node, and then identifying one or more distance measurement paths between the initiator and target nodes.In some embodiments, the identification of the distance measurement path is performed by a central controller that communicates with, or is assisted by, the initiator and target networks. This step involves the transmission of distance parameters between the initiator and target networks. The distance measurement path includes the designated node, i.e., a UWB-enabled or other intelligent node located in the target network. The procedure involves requesting the target node to perform the desired action or provide the desired service via the distance measurement path.

[0009] Identifying the distance measurement path can include: estimating, via a central controller using a near-field distance measurement protocol, the respective near-field distances to one or more neighboring nodes of the plurality of relay nodes within a maximum range of the initiator node, wherein the respective nodes of the one or more neighboring nodes are in the initiator network of the initiator node or in the target network of the target node. Such an embodiment can include: dynamically determining the internode distance between the initiator and the target node, at least partially, based on the respective near-field distances to the one or more neighboring nodes.This embodiment also includes: requesting the desired action or service via one or more neighboring nodes when it is determined that the internodal distance between the initiator and target nodes is not greater than an activation threshold.

[0010] The central controller can be configured as or contain a cloud-based server, and in this case, the identification of the distance measurement path is performed using the cloud-based server.

[0011] Determining the internodal distance between the initiator and target nodes can further be based on estimating the angle of incidence of a signal exchanged between the initiator node and a neighboring node from the plurality of relay nodes, and on estimating the angle of incidence of a signal exchanged between the target node and the neighboring node. The procedure can also include estimating the distance to the neighboring node based on the arrival time of a signal sent from the initiator node to the neighboring node. After estimating the distance to the neighboring node, the procedure can instruct the neighboring node to estimate the distance between itself and the target node.

[0012] The designated node in one or more implementations is configured with authentication, security, and / or privileges to interact with one or more of the relay nodes. Additionally, the designated node may be configured with authentication, security, and / or privileges to interact with the initiator node or the target node, whereby the initiator node and / or the target node is unable (or not permitted) to interact directly with any other node in a network to which the designated node belongs.

[0013] Embodiments of the method include: establishing a communication link between the initiator network and the target network via a central controller using a plurality of wireless routers. In such an embodiment, accessing the recorded activation profile in the computer-readable storage medium may include accessing the recorded activation profile in the memory of the central controller and establishing communication links between the central controller, the initiator node, and the target node. The method may also include communication via a wireless router with: (a) the initiator node and a first set of relay nodes, and (b) a second set of relay nodes and the target node via a perimeter router, wherein the plurality of wireless routers comprises the wireless router and the perimeter router.

[0014] In summary, the present method, in one or more embodiments, may include measuring the arrival time and angle of a signal sent from the initiator node to one or more relay nodes. The measurement of the signal's arrival time and angle can be performed using the designated node, wherein the designated node is an ultra-wideband (UWB) capable node.

[0015] The target network can be configured as a proprietary network, in which case the method can use the designated node as a proxy node to initiate a near-field distance measurement session during a commissioning process of the initiator or target node. The commissioning process can include authorizing the use of the initiator or target node during the near-field distance measurement session.

[0016] Aspects of the invention include the use of a shortest distance algorithm to determine a node path from the initiator node to the target node via one or more relay nodes, as well as the regular checking of a status and connectivity of one or more relay nodes at a sampling frequency and the adjustment of the sampling frequency based on a property of one or more relay nodes.

[0017] The initiator node can be a smartphone or a vehicle (or part thereof). The target node can be a smart home device (or part thereof). In such an embodiment, access to the recorded activation profile can include access to a recorded light, door, appliance, and / or vehicle charging station setting of the smart home device.

[0018] Another aspect of the invention comprises a networked ecosystem with a node capable of communicating distance parameters between an initiator network and a target network, a wireless router, a fringe router, and an initiator node located within the initiator network. The networked ecosystem further comprises a plurality of relay nodes, including at least one transit node and at least one smart node. The at least one smart node includes a designated node.

[0019] A target node is located within the target network or is a member thereof. The target network, in turn, is outside the maximum range of the initiator node. The node capable of transmitting the distance parameters communicates with the initiator network and the target network via the wireless router or the edge router.

[0020] In this embodiment, a computer-readable storage medium contains a recorded activation profile that includes a desired action or service of the target node. The networked ecosystem is configured to use a centralized near-field distance measurement protocol to access the recorded activation profile and identify a distance measurement path between the initiator node and the target node, where the distance measurement path includes the designated node. The networked ecosystem then requests the execution of the desired action or service via the distance measurement path.

[0021] In another implementation, the networked ecosystem comprises an initiator node located in a first area as part of an initiator network, where the initiator node has UWB capability, and a variety of relay nodes, including at least one transit node and at least one smart node. The smart node also has UWB capability and is designed as a designated node. The target node, located in a second area as part of a target network, lies outside a maximum range of the initiator node and, in this representative design, is configured as an automation robot. A computer-readable storage medium contains an activation profile in the form of a desired action or service from the target node.

[0022] In this embodiment, a cloud-based central controller can be used to communicate distance parameters between the initiator network and the target network. A first wireless router connects the initiator network to the cloud-based central controller. A second wireless router connects the target network to the cloud-based central controller. The central controller uses a centralized near-field distance measurement protocol to access the recorded activation profile and determine a distance measurement path between the initiator node and the target node. The potential distance measurement path includes the designated node. The central controller can then request the execution of the desired action or service via this distance measurement path.

[0023] The features summarized above, as well as other features and advantages of this invention, will be readily apparent from the following detailed description of illustrative examples and methods for carrying out the present invention in conjunction with the accompanying drawings and claims. Furthermore, this invention expressly includes combinations and subcombinations of the elements and features presented above and below. BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1A is a representation of a representative networked ecosystem configured to use a centralized, extended multi-hop near-field distance measurement strategy as described here. Fig. Figure 1B is a representation of an alternative industrial networked ecosystem in which the centralized extended multi-hop near-field distance measurement strategy of the present invention can be used. Fig. Figure 2 is a block diagram showing a protocol for implementing the centralized extended multi-hop distance measurement strategy of the present invention. Fig. Figure 3 is a schematic representation of an environment with multiple buildings in which the present centralized, extended multi-hop near-field distance measurement strategy can be applied. Fig. 4A and Fig. 4B represent models for implementing the centralized extended multi-hop near-field distance measurement strategy according to aspects of the invention. Fig. Figure 5 is a flowchart describing a method for implementing the centralized extended multi-hop near-field distance measurement strategy according to an embodiment of the invention.

[0024] The present invention can be modified or implemented in alternative forms, with representative embodiments shown in the drawings and described in detail below. DETAILED DESCRIPTION

[0025] Referring to the drawings, in which the same reference numbers refer to the same features in the different views, it is stated in Fig. Figure 1A depicts a local, networked Internet of Things (IoT) ecosystem 10, in which several communication nodes are in networked communication with each other, as shown here. The in Fig. The connected ecosystem 10 shown in Figure 1A is described as an automated smart garage of a smart home 11. In such an embodiment, the aforementioned nodes may include one or more of the following devices, e.g., a wireless / Wi-Fi-enabled thermostat 12, a garage door 13, a security camera 14, a device 15, a smartphone 16, or another smart device, e.g., a smartwatch or other wearable, etc., a light bulb 17, a vehicle 18, etc. As described further below, the connected ecosystem 10 also includes a computer-readable storage medium 19 on which an activation profile 190 is recorded or stored, wherein the activation profile is a desired action or service of a target node or device, as described below. The activation profile 190 can therefore be accessed from the computer-readable storage medium 19 within the scope of the present concept.The actual host or location of the computer-readable storage medium 19 may vary depending on the embodiment and is therefore in . Fig. 1A is shown separately from the various networked devices.

[0026] In Fig. 1B is an alternatively structured, networked ecosystem 10A in the form of an automated industrial plant, e.g., a production facility or a warehouse. Walls 40 (one of which is in Fig. (1B shown) and a floor 41 define work areas for carrying out various related activities. The networked ecosystem 10A can, for example, include an inventory area 42, e.g., shelves or parts / component containers, one or more production lines 43, a receiving area 44, and an office space 45, as well as other possible areas or work areas. In such an embodiment, the nodes mentioned above can correspond to various computers, wireless devices, sensors, smart devices, etc., including passive RFID (Radio Frequency Identification) tags, barcodes / barcode readers, and the like. How the networked ecosystem 10 of Fig. 1A also includes the interconnected ecosystem 10A from Fig. 1B a computer-readable storage medium 19 on which the activation profile 190 is recorded or stored, or which can be accessed. The actual host / location of the computer-readable storage medium 19 within the depicted networked ecosystems 10 and 10A may vary depending on the embodiment and is therefore separate from the various networked devices in Fig. 1A and Fig. 1B is shown.

[0027] The descriptions of the smart home and smart garage implementations, as well as the intelligent facilities in the Fig. 1A and Fig. 1B are used below for illustrative purposes only, and the actual number and structure of the individual nodes involved in the networked ecosystems 10 and 10A will vary depending on the intended application. For the sake of simplicity and consistency, the networked ecosystems 10 and 10A will be referred to as Fig. 1A and 1B are described below with reference to the networked ecosystem 10A.

[0028] With brief reference to Fig. 4A and Fig. 4B, both of which are discussed in more detail below, comprises the networked ecosystem 10A of Fig. 1B an initiator node 201, e.g. with an ultra-wideband (UWB) capability, and a plurality of connected relay nodes 20R, wherein the relay nodes 20R include at least one transit node with a lower capability and at least one "smart" node with a higher capability, as described in detail below. The networked ecosystem 10A also includes a destination node 20T, which is located outside the range (limit) of the initiator node 20I and thus outside direct communication with it. The computer-readable storage medium 19 mentioned above contains, in this embodiment, the recorded activation profile 190. The networked ecosystem 10A described here is further configured to use a proximity ranging protocol 30 ( Fig. 2) used to estimate the respective distances to one or more neighboring nodes of the multiple relay nodes 20R within the range of the initiator node 20I, and to dynamically determine an internodal distance between the initiator node 20I and the target node 20T using the respective ranges or distances.

[0029] As considered herein, the near-field distance measurement between nodes of the networked ecosystem 10A includes Fig. 1B and alternative embodiments thereof, including the connected ecosystem 10 of Fig. 1A, an accurate estimation of the distances between the nodes or the internodal distances. For example, according to Fig. 3. A manufacturing, assembly, packaging, or order fulfillment operation may extend across multiple areas or buildings. Multiple buildings within a production facility typically have multiple controllers or routers, which in turn are connected to a central controller, such as a local controller or a cloud-based controller. Cloud support may be required for distance measurement between two devices located in two different buildings. In such cases, the centralized, extended multi-hop distance measurement method of the present invention can be used.

[0030] A simplified scenario is in Fig. Figure 3 shows two areas in the form of exemplary buildings: a first building (Building No. 1) with the initiator network and a second building (Building No. 2) with the target network, separated by walls 40. In Building No. 1, a conveyor 50 can pass by the local controllers 20A and 20B. The products can be marked with barcodes 25 to track the production progress. Exemplary devices acting as nodes here could include an intelligent light thread. ®The system includes device 23C and an RFID sensor 23D for tracking objects. As is known in engineering, Thread is a low-power, low-bandwidth mesh network protocol, similar in some respects to the open-source protocols Zigbee, Z-Wave, and other "smart home" IoT protocols, but without requiring a central hub or bridge. In building 2, another local controller 20C can be used in conjunction with conveyor 50 and potentially one or more automation robots 23A and 23B. Enabling the extended-range service in this scenario can cause the local controller 20A to request assistance from the out-of-range automation robot 23B. The robot 23B can be assigned multiple tasks and therefore needs to perform several different functions, such as asset management, quality control, fault analysis, repair, maintenance, etc.

[0031] In this representative embodiment of the networked ecosystem 10A of Fig. In diagram 3, where the communication links are designated CL and the distance measurement links as RL, a transmitting node such as the local controller 20A or 20B of building no. 1, e.g., the manufacturing controllers, may be required to locate the automation robot 23A or 23B in building no. 2, possibly via one or more (i.e., an integer "n") additional local controllers (manufacturing unit n). However, the automation robot 23A, 23B is outside the range of the local controllers 20A and 20B. Therefore, detection and localization can be achieved here via one or more intermediate RFID sensors 23D for tracking objects or other device nodes, e.g., to request the inspection of a potentially defective part while the part is being transported on a conveyor 50.

[0032] Regardless of the design of the networked ecosystem 10A from Fig. 1B and Fig. 2. The networked ecosystem 10A benefits in many ways from the centralized, extended multi-hop proximity ranging or near-field distance measurement technology described here.

[0033] For example, modern near-field distance measurement techniques for typical smart home / garage, production facility, and other local network applications are implemented according to the open-source standard Matter™ (MATTER), which is designed to manage communication between locally networked devices. In some applications, a device / node can send activation commands to a target node that are based, at least in part, on the proximity or near field of the target node. Users of the networked ecosystem 10 of Fig. 1A, the industrial IoT use case of Fig. However, 1B or other home, office, industrial, medical or other use cases can benefit from the reduced latency and the resulting improved customer experience.

[0034] For example, a user traveling from the kitchen to the garage of their smart home can ( Fig. 1A) Upon reaching the garage, the user expects the garage door 13 to be fully open and their vehicle 18 to be disconnected from a charging station (not shown) and / or conditioned according to the user's custom settings as they approach the vehicle 18. Conditioning may include one or more seat settings, mirror settings, interior temperature settings, and other settings. The overall user experience may be somewhat diminished if the user has to wait for the planned actions to complete before entering the vehicle 18. Therefore, the extended multi-hop strategy aims to extend communication distances and reduce response latency, avoid out-of-range activation errors, and improve the overall customer experience within a local network such as the representative connected ecosystem 10 of Fig. 1A or Fig. 10A of Fig. 1B to improve.

[0035] Although not shown in the various figures for the sake of simplicity, the hardware connected to the various nodes of Fig. 1A and Fig. 1B is connected in the form of one or more application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), electronic circuits, central processing units, e.g., microprocessors or processors, and associated computer-readable storage media / memory. Non-transitory components of such memory, such as the computer-readable storage medium 19 of Fig. 1. These devices are capable of storing machine-readable instructions in the form of one or more software or firmware programs or routines, combinational logic circuits, input / output circuits and devices, signal conditioning and buffering circuits, and other components that one or more processors can access to provide a described functionality. With this hardware and the associated antennas, receivers, and transmitters located at the various nodes, information can be exchanged wirelessly between the nodes, e.g., via Wi-Fi, Zigbee, Bluetooth™, Bluetooth™ Low Energy (BLE), etc.

[0036] As in Fig. As shown in Figure 2, an extended multi-hop near-field distance measurement protocol 30 can be used for the decentralized and centralized alternative embodiments described below with reference to Fig. 4A and 4B are described. The extended multi-hop near-field distance measurement protocol 30 is shown as a block diagram for clarity. In an IoT context, actions are triggered at a target node based on predefined or pre-recorded user profiles. For example, a user of the connected ecosystem 10 can Fig. User 1A, walking from a kitchen to a garage in the depicted smart home 11, expects the temperature setting and / or the seats and mirrors of the vehicle 18 to be adjusted according to their individual settings upon reaching the garage. Similarly, a user walking around the smart home 11 can set profiles for when the light bulb 17 should be switched on, the vehicle 18 should be charged or stopped charging, etc., depending on the user's position within the smart home 11. Similar expectations can be found in the industrial embodiment of Fig. 1B for other networked devices.

[0037] Although such profiles are already established, the enhanced multi-hop near-field distance sensing strategy described here allows for an increase in the distance between the start and target nodes compared to existing strategies, as mentioned above. This greater range can lead to a better user experience, especially since some actions, such as opening / closing doors, disabling electric vehicle (EV) charging devices, or customizing settings within a vehicle to prepare a specific driver, take time after initiation. Therefore, earlier activation of these actions, enabled by enhanced near-field distance sensing, helps to reduce or eliminate the time the user has to wait for their execution. Programmed actions can thus begin earlier than would be possible without the benefits of this teaching.

[0038] In Fig. Block 32 represents such activation profiles that can be transmitted to an IoT-enabled controller 20CC, as indicated by arrow 33. Such a controller 20CC can be used in various ways as a master / “smart” node in a centralized ecosystem model 10-1, as shown in Fig. 4A shown, or 10-2 ( Fig. 4B), as described below. The extended multi-hop near-field distance measurement protocol 30 also includes a near-field distance measurement block 34, which, as indicated by arrow 35, is located on an initiating node 20I, e.g., the vehicle 18 of Fig. 1, the smartphone 16, etc. The block 34 for near-field distance measurement can provide the activation rules 34R required for operation according to the invention.

[0039] The extended multi-hop near-field distance measurement protocol 30 of Fig. 2 also includes various relay nodes 20R, including IoT-enabled / detectable connected relay devices 20R within the networked ecosystem 10, which operate either as lower-capacity transit nodes or as higher-capacity smart nodes, as explained below. Block 36 represents such advanced technological capabilities as lower power limitations, higher computing capacities, the ability to estimate the angle of arrival (AoA), or others for the smart nodes, while Block 38 represents the lower capabilities of transit nodes, e.g., RFID tags and possibly other low-power IoT devices, which are typically in a sleep mode and therefore require time to wake up and perform actions such as distance measurement. The advanced multi-hop near-field distance measurement protocol 30 also considers the operation of the target node 20T, i.e.,the intended executors of actions initiated via service activations from the initiating node 20I. The following examples are based on the architecture of the extended multi-hop near-field distance measurement protocol 30. Fig. 2. CENTRALIZED ADVANCED MULTI-HOP DISTANCE MEASUREMENT:

[0040] In Fig. Figure 4A shows the centralized ecosystem model with 10-1 different devices / nodes, which are nominally labelled A to H for simplicity. Fig. 4A is an exemplary implementation where a central controller, in this case a cloud-based or another central controller 20, is used to reach a target node 20T out of range and activate a desired action or service there. Such use can be achieved via cloud-based or external edge networks. While the present teaching is sufficiently flexible to perform centralized multi-hop distance measurement with or without network segmentation, Fig. 4A represents a representative case in which two areas (area no. 1 and area no. 2), e.g. the exemplary factory floor of Fig. 3, separated from each other by a boundary 21, e.g. the walls 40 of Fig. 1B, if areas No. 1 and No. 2 represent different structures, designated workspaces, buildings, or other areas. The teachings presented here can be used for managing meeting resources and communication in this or other densely populated network environments.

[0041] In Fig. 4A represents node A as an initiator node 20I, i.e., a node / device that initiates a request to communicate with a destination node 20T (node ​​H) located outside the range of the initiator node and to request a desired action or service from it. Nodes B, C, D, E, F, and G represent relay nodes, most or all of which may be configured as the transit nodes described above, and none, one, or several of which may be configured as more computationally powerful intelligent nodes. The centralized ecosystem model 10-1 of Fig. 4A also includes additional network nodes, in this case a cloud-based controller 20, a wireless router 22, e.g., a Wi-Fi, Thread®, MATTER, or Zigbee router, and a perimeter router 24, also a Wi-Fi, Thread®, MATTER, or Zigbee perimeter router. In this embodiment, nodes B and E function as so-called "anchor" nodes (described below), with this anchor status being defined in Fig. 4A is indicated by an asterisk (*). In general: If a device operating in area No. 1 uses wireless router 22, acting as a Zigbee network router, to activate a device in area No. 2 that, for example, operates a MATTER network via edge router 24, then the device's range / localization extends to a specific designated node in the MATTER network, in this case node E (*). The designated node E would then reach the target node 20T via one or more intermediate nodes within the MATTER network, for example, node G.

[0042] In a home charging application where the smart home 11 ( Fig. 1A) is connected to an electric vehicle supply equipment (EVSE) in the form of an electric charger, the charger can act as a designated node, with a user approaching the smart home 11 passing through the designated node. Thus, the use of designated nodes can be used to increase security. For example, defining a distance measurement path between the initiator node 20I and the target node 20T, e.g., via the central controller 20, can involve the use of a distance measurement path that includes the designated node. This action can, in turn, be carried out via the central controller 20 using the near-field distance measurement protocol of Fig. 2. The estimation of the respective distances to one or more neighboring nodes of the multitude of relay nodes within the maximum range of the initiator node 20I shall include. In this example, the respective nodes of the one or more neighboring nodes are located in the initiator network or the target network. After estimating the distance(s) to the neighboring node(s), each neighboring node can be instructed to estimate the distance between itself and the target node 20T.

[0043] In Fig. 4A The present approach can assume that the initiator node 20I is already part of the exemplary MATTER network. This assumption can be extended further. The initiator node 20I or the target node 20T may, in some cases, undergo a commissioning process to join the MATTER network, but can still use the aforementioned designated node as a proxy to initiate / participate in a new multi-hop near-field distance measurement session. The vehicle 18 ( Fig. 1A) may, for example, not be part of the MATTER network, but may still use an electric vehicle charging station (EVSE) (e.g., part of an OEM network or the exemplary MATTER network) as a proxy to control another device, such as a television or lighting system, later in the commissioning process.

[0044] In the depicted deployment environment, each node has two functions: (i) communication and (ii) distance measurement. The distance measurement function includes the time of arrival (ToA) for distance measurement and the angle of arrival (AoA) for localization. Functions (i) and (ii) can be performed using the same wireless technology, e.g., Wi-Fi, or using different wireless technologies, such as Wi-Fi for communication and ultra-wideband (UWB) for distance measurement / localization. Furthermore, each node is connected to the central controller 20 (a local or cloud-based server or backend) via appropriate wireless communication networks, e.g., Wi-Fi, THREAD, Zigbee, etc., using appropriate gateways. The initiator node 20I is part of an initiator network, while the destination node 20T is part of a destination network, e.g., a proprietary network.The initiator node 20I must therefore communicate with the target node 20T via the intermediate central controller 20 in the various embodiments. This is shown by the dashed lines BE and CF in the figure. Fig. As shown in Figure 4A, the present multi-hop approach offers the flexibility to enable or disable internetwork distance measurement / localization. In some implementations, the central controller 20 therefore determines the distance measurement path(s) from one node to another, in particular from the initiator node 20I to the target node 20T.

[0045] As is known in the professional world, the Randrouter 24 can be made of Fig. 4A is used to connect a local network to the internet or to a larger network or networks via the wireless router 22. As the name suggests, the edge router 24 can be located at the edge of a network, in this case the initiator network / first wireless network served by the wireless router 22. Functionally, the edge router 24 routes data traffic and thus acts as a gateway between a local network and one or more external networks. The wireless router 22, in turn, is used to communicate with nodes within a specific local network, e.g., with nodes A, B, C, and D in the simplified representation of Fig. 4A, as shown by the connection lines 220. The wireless router 22 can also be connected to the internet, e.g., via an Ethernet box (not shown) to which the wireless router 22 is connected, via a fiber optic or coaxial cable, via a mobile network connection, or otherwise. The edge router 24 connects other nodes, nominally nodes E, F, G, and H, to the wireless router 22 via the central controller 20, as indicated by arrows CC1 and CC2. Fig. 4A represents lines 220 and 240 wireless communication paths within the networked ecosystem 10.

[0046] The centralized nature of the present extended multi-hop strategy is based on the following assumptions: (1) Some of the nodes are ultra-wideband (UWB)-capable nodes, e.g., the smartphone 16 or other mobile device, or the vehicle 18 of Fig. 1A, a moving automation robot 23A or 23B ( Fig. 3), etc., (2) each UWB-enabled node has the capability to measure the time of arrival (ToA) or angle of arrival (AoA), e.g., using multiple antennas, so that one or more UWB-enabled nodes are able to determine the relative location of other UWB nodes, and (3) each UWB-enabled node is connected to the cloud-based controller 20, e.g., to an external central server, which is able to determine distance parameters between an initiating network in area No. 1 and a destination network in area No. 2. Fig. 3. to communicate over different wireless networks, as shown. As is known in the industry, UWB-enabled sensors are configured to use a specific portion of the radio spectrum, typically 3.1 GHz to 10.6 GHz, for high-speed data transmission over relatively short distances.

[0047] Among other advantages, low-power UWB-enabled sensors, when used in the context of the centralized ecosystem model 10-1 of Fig. 4A accurate localization and real-time tracking of objects of interest. Since the aforementioned frequency range is widely spread, UWB sensors are less susceptible to interference from Wi-Fi or Bluetooth™ devices, making UWB sensors ideal for IoT applications of the type considered here. Thus, detecting the respective distances to one or more neighboring nodes within the scope of the invention can include the use of one or more UWB-enabled nodes to measure the time of arrival (ToA) and angle of arrival (AoA) of a signal from the one or more neighboring nodes.

[0048] The characteristics of the centralized multi-hop strategy of Fig. 4A includes the creation of local distance maps, centralized multi-hop localization, and dynamic neighborhood search. For the creation of local distance maps, each UWB-enabled node periodically scans its neighboring nodes, with the scan frequency determined by network mobility or by assessing the capabilities of the neighboring nodes. One option involves communication from a local network in area 1 to the cloud-based controller 20 and ultimately to the target node 20T via the central controller 20. Another option can be used if the BE and DF links do not exist, in which case the initiating network can be localized within its area, i.e., area 1, and communicate via the central controller 20 to determine the locations of nodes in area 2.A possible approach to implementing centralized extended multi-hop localization is described below with reference to . Fig. 5. In dynamic neighborhood search, a shortest distance or shortest path algorithm can be used to find the path, increasing the sampling or scanning frequency at the nodes along the distance path. Thus, the near-field distance measurement method described here can use a shortest distance algorithm to determine a node path from the initiator node 20I, via one or more neighboring nodes, to the target node 20T.

[0049] In Fig. 4B briefly shows an alternative centralized ecosystem model 10-2, which is a configuration on a smaller scale than the one in Fig. 4A is shown. The functions of the central controller 20 are shown. Fig. 4A can also be executed by other nodes. A bridge CC3 exists between routers 22 and 24, e.g., a wireless point-to-point network connection. In a possible use case, a mobile device acting as an initiator node 20I in an original equipment manufacturer (OEM)-specific network can attempt to activate a device in a MATTER network. The mobile device, e.g., the smartphone 16, from Fig. 1A, in this case, can connect to a specific node in the MATTER / OEM network, so that the mobile device can only reach the target node 20T via intermediate nodes of the MATTER network, e.g., nodes E, F, and G in the simplified example network of Fig. 4B, which contains the designated node. The designated node can be configured with authentication, security, and / or privileges for interacting with the initiator node 20I or the target node 20T. In one or more embodiments, the initiator node 20I and / or the target node 20T is also unable (or not permitted) to interact directly with other nodes in a network to which the designated node 20T belongs.

[0050] As in Fig. As shown in Figure 5, the creation of a local distance map, as described above, can be carried out using an algorithm or a procedure 100. For the sake of clarity, each process step of the procedure 100 is described as a separate code set and organized as logic blocks. Depending on the action, the different blocks can be accessed from a specific node of the networked ecosystem 10 ( Fig. 1A) or Fig. 10A ( Fig. 1B) will be carried out.

[0051] After starting the procedure 100 in block B101 and again with reference to the exemplary embodiments of Fig. 4A and Fig. 4B continues procedure 100 with block B102 ("location initialization"), whereupon the initiator node 20I initializes the location of the out-of-range target node 20T. Procedure 100 then proceeds to block 104.

[0052] Block B104 (“Scanning Neighbors”) involves communication with neighboring nodes (one or more of the relay nodes) via the initiator node 20I within its communication range. Since some of the neighboring nodes may be in a sleep or power-saving mode, these nodes are induced to wake up in block B104, as indicated by the arrow WW. Block B104, or other parts of the method 100 in some embodiments, therefore include establishing communication links between the central controller 20, the initiator node 20I, and the destination node 20T, and then communicating via a wireless router with: (a) the initiator node 20I and a first group of relay nodes, and (b) a second set of relay nodes and the destination node 20T via the edge router 24 ( Fig. 4A). In this case, the multitude of wireless routers includes wireless router 22 and edge router 24. Procedure 100 then transitions to block 105.

[0053] In block B105 (“Smart node?”) of Fig. In step 5 of procedure 100, it is determined whether the neighboring node scanned in block B104 is a master / smart node, as described above. Therefore, in block B104, the computational functionality of the neighboring nodes is determined, i.e., whether one or more neighboring nodes are low-performance transit nodes or high-performance smart nodes, i.e., nodes with multiple antennas capable of determining the time of arrival (ToA) and angle of arrival (AoA). Procedure 100 continues with block B106 if the neighboring node is a smart node, and with block B107 if the neighboring node is a transit node.

[0054] Block B106 ("Locate Neighbor") involves the initialization of the localization of a neighboring node with intelligent capabilities. Procedure 100 then proceeds to Block 108.

[0055] Block B107 (“Distance Measurement m / Neighbor”) involves locating a neighboring node that lacks the required multi-antenna structure necessary for activating intelligent functions. Procedure 100 then proceeds to Block 109.

[0056] Block B108 (“ToA, AoA”) from Fig. Section 5 involves determining the time of arrival (ToA) and angle of arrival (AoA) of the neighboring node located in block B106. The time of arrival is the time it takes for a receiving node to receive a transmitted signal from a neighboring node. After measuring the time of arrival, the distance between the nodes can be easily calculated as the product of the ToA and the signal speed, i.e., the speed of light. The angle of arrival (AoA), as the name suggests, determines the direction from which a signal arrives at a receiving node, where an antenna array detects the signal with a slight phase and amplitude difference. The AoA is then determined based on the measured phase and amplitude differences, for example, using beamforming or other suitable algorithms.The measurement of the arrival time and angle of arrival of the transmitted signal is performed using the designated node, as mentioned above, wherein the designated node is configured as an ultra-wideband (UWB)-capable node in one or more embodiments. Method 100 proceeds to block B110 once the ToA and / or AoA have been determined.

[0057] In block B109 (“ToA”), the initiator node determines the arrival time (ToA) of the neighboring node located in block B106. Since the receiving node is a transit node in this case, arrival time information is available to the receiving node, while arrival angle (AoA) information is not. Procedure 100 continues with block B110 once the ToA has been determined.

[0058] In block B110 (“packet”), the initiator node 20I generates a data packet containing relevant information for communication with the neighboring node. The data packet can contain, for example, the unique identifier of the initiator node, arrival time (ToA) and / or arrival angle (AoA) information from blocks B108 or B109, as described above, as well as a unique identifier of the neighboring node (e.g., an alphanumeric string or a bit code, etc.). Procedure 100 then proceeds to block 112.

[0059] In block B112 (“Send package”) of Fig. 5. The initiator node 20I transmits the packet from block B110 to the central controller 20 if the representative embodiment of Fig. 4A or Fig. 4B is used as described above. Embodiments of the near-field distance measurement method therefore generally include transmitting the data packet to the one or more neighboring nodes, wherein the data packet contains a unique identifier and the location of the initiator node 20I, the ToA and the AoA, and a unique identifier of the one or more neighboring nodes. In response to receiving the data packet from the initiator node 20I, block B112 or another block may include sending a response data packet via each of the one or more neighboring nodes, including sending the unique identifier of each of the one or more neighboring nodes, the arrival angle of the data packet, and the arrival time of the data packet. Method 100 then proceeds to block 114.

[0060] Still referring to Fig. 5, Procedure 100 next involves performing a centralized multi-hop localization algorithm using the information in the package from block B112, e.g. via the central controller 20 of Fig. 4A or point-to-point communication in Fig. 4B. A representative set of codes that can be used for this purpose is as follows.

[0061] In the algorithm above, graph G defines the aforementioned anchor node as a node whose position (self-location) is predetermined during installation and held during algorithm execution. In the representative Smart Home 11 of Fig. 1A The anchor knot can be device 15, a television, etc. In the industrial plant environment of Fig. 1B The anchor node can be a specific machine, a cabinet, or another node. Anchor nodes are adjacent nodes, even if they are not in close proximity. The location of the anchor nodes can be determined based on a map if the anchor nodes are not within mutual range. This distance can be set to zero so that the location of the target node 20T can be quickly determined.

[0062] Non-anchor nodes determine their own location iteratively via a neighboring smart node with self-locating capabilities or via three neighboring transit nodes with self-locating capabilities. In dynamic sampling, some implementations can implement a weighted solution by ranking nodes with higher distance measurement frequencies if these nodes are on a distance measurement path.

[0063] Continuing the discussion from Fig. 5. The initiator node 20I in block B116 ("Dynamic Neighbor Scanning") receives the distance measurement path from block B114 and performs a dynamic neighborhood query routine. As is known in the field, such a technique can be used to monitor and manage the status of various neighboring nodes. Generally, each node maintains a local list or table of its neighboring nodes, i.e., those located within a distance limit or maximum communication range, which, depending on the implementation, can be several dozen meters or less. During the dynamic neighborhood query, the initiator node 20I or another scanning node checks the status and connectivity of the neighboring nodes at regular intervals with a sampling frequency.The sampling frequency can be dynamically adjusted up or down as needed, based on characteristics of one or more neighboring nodes, such as node behavior / presence of changes or anomalies, movement of the neighboring node, speed of movement, speed at which a selected neighboring node leaves the maximum near-field distance measurement area, etc. Higher sampling frequencies can be used if the node is mobile or located on the path determined in block B114. Procedure 100 then returns to block B104.

[0064] The activation of the centralized enhanced multi-hop distance measurement service according to the present invention overcomes certain limitations of current distance measurement techniques, which require two communicating devices to be in close proximity to each other. In the embodiments of Fig. 1A and Fig. However, in 1B, there is a need to communicate with devices that are outside the range of the initiating device. Extended distance measurements using the multi-hop strategy discussed here are therefore performed to trigger a requested service or activity from a target device with lower latency. If the number and / or density of such devices is relatively high, as in the exemplary connected ecosystem 10A of Fig. 1B, the identification of suitable intermediate nodes between the initiator node 20I and the destination node 20T can be achieved using the present centralized strategy for identifying suitable distance measurement paths between nodes. If nodes requiring distance information are not all located in a specific communication network, e.g., in area No. 1 or area No. 2 of Fig. 3, and therefore communication with an intermediate node such as the central controller 20 of Fig. Since 4A is required, the present strategy enables the orchestration of the extended range. In a proprietary network application, as mentioned above, a designated node can be used as a proxy node to initiate a near-field distance measurement session. The commissioning process may involve authorizing the use of the initiator node 20I or the target node 20T during the near-field distance measurement session. These and other related advantages are readily apparent to professionals in light of the foregoing.

Claims

[1] Centralized near-field distance measurement method for use in a networked ecosystem (10, 10A), wherein the networked ecosystem (10, 10A) comprises an initiator node (201) located in an initiator network, a plurality of relay nodes, including a designated node, and a target node (20T) located in a target network and outside the range of the initiator node (201), wherein the centralized near-field distance measurement method comprises: Accessing a recorded activation profile in a computer-readable storage medium (19) as a desired action or service of the target node (20T); Identifying a distance measurement path between the initiator node (201) and the target node (20T), including transmitting distance measurement parameters between the initiator network and the target network, wherein the distance measurement path includes the designated node; Requesting the execution of the desired action or service via the distance measurement path, wherein the designated node is a smart node located in the target network of the target node (20T) and which has multiple antennas and is capable of determining the time of arrival (ToA) and angle of arrival (AoA) of a signal; and Establishing a communication link between the initiator network and the target network via a central controller (20) using a plurality of wireless routers (22, 24), wherein a first wireless router (22) connects the initiator network to the cloud-based central controller (20) and that a second wireless router (24) connects the target network to the cloud-based central controller (20); wherein identifying the distance measurement path comprises: estimating, via a central controller (20) using a near-field distance measurement protocol, respective near-field distances to one or more neighboring nodes of the plurality of relay nodes within a maximum range of the initiator node (201), wherein respective nodes of the one or more neighboring nodes are in the initiator network of the initiator node (201) or in the target network of the target node (20T). [2] The method of claim 1, further comprising: dynamically determining an internode distance between the initiator node (20I) and the target node (20T) at least partially based on the respective near-field distances to one or more neighboring nodes; and Requesting the desired action or service via one or more neighboring nodes when it is determined that the internodal distance between the initiator node (201) and the target node (20T) is not greater than an activation threshold. [3] Method according to claim 1, wherein determining the internodal distance between the initiator node (201) and the target node (20T) is further based on estimating an arrival angle of a signal exchanged between the initiator node (201) and a neighboring node of the plurality of relay nodes, and estimating an arrival angle of a signal exchanged between the target node (20T) and the neighboring node. [4] The method of claim 3, further comprising: Estimating a distance to the neighboring node based on the arrival time of a signal sent from the initiator node (201) to the neighboring node. [5] The method of claim 4, further comprising: After estimating the distance to the neighboring node: instruct the neighboring node to estimate the distance between itself and the target node (20T). [6] Method according to claim 1, wherein the designated node is configured with authentication, security and / or privileges to interact with one or more of the relay nodes. [7] Method according to claim 1, wherein the designated node is configured with authentication, security and / or privileges to interact with the initiator node (201) or the target node (20T), and wherein the initiator node (201) and / or the target node (20T) is unable or not authorized to interact directly with any other node in a network to which the designated node belongs.

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